1992
DOI: 10.1177/0013164492052004007
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Correlational Meta-Analysis: Independent and Nonindependent Cases

Abstract: The purpose of this study was to determine the effect of the violation of the assumption of independence when combining correlation coefficients in a meta-analysis. In this Monte Carlo simulation the following four parameters were used with the values specified: N-the sample size within a study (20, 50, 100), p-the number of predictors (1, 2, 3, 5), rho( i)-the population intercorrelation among predictors (0, .3, .7), rho( p)-the population correlation between predictors and criterion (0, .3, .7). When cnly on… Show more

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Cited by 53 publications
(41 citation statements)
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“…Second, if effect sizes were reported separately by outcome type (e.g., if both a knowledge and skill measure were reported), these effects were considered independent cases (Bijmolt and Pieters 2001;Tracz et al 1992). Third, within outcome type (e.g., if multiple knowledge measures were reported), mean effect size estimates were calculated.…”
Section: Inclusionary Criteriamentioning
confidence: 99%
“…Second, if effect sizes were reported separately by outcome type (e.g., if both a knowledge and skill measure were reported), these effects were considered independent cases (Bijmolt and Pieters 2001;Tracz et al 1992). Third, within outcome type (e.g., if multiple knowledge measures were reported), mean effect size estimates were calculated.…”
Section: Inclusionary Criteriamentioning
confidence: 99%
“…Using more than one effect size estimate from the same study violates the assumption that the effect sizes are independent. However, this kind of violation does not substantially affect statistical precision (Tracz, 1984(Tracz, /1985Tracz, Elmore, & Pohlmann, 1992). If we had not used more than one effect size estimate from experiments that manipulated a potential moderator variable, we could not have properly conducted the moderator analyses, because we would have had to discard (or code into a mixed category) some of the most relevant information.…”
Section: Effect Size Analysesmentioning
confidence: 99%
“…Although caution has been advised regarding the analysis of nonindependent effects (e.g., Wolf, 1986), we included all effects from a particular study if the data were available. Besides, it has been argued that the nonindependence violation does not greatly affect statistical precision (Block, Zakay, & Hancock, 1998;Tracz, Elmore, & Pohlmann, 1992).…”
Section: Effect Size Calculationsmentioning
confidence: 99%